CN113325385B - Anti-interference method for phased array-MIMO radar mode transmit-receive beam forming - Google Patents

Anti-interference method for phased array-MIMO radar mode transmit-receive beam forming Download PDF

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CN113325385B
CN113325385B CN202110798269.9A CN202110798269A CN113325385B CN 113325385 B CN113325385 B CN 113325385B CN 202110798269 A CN202110798269 A CN 202110798269A CN 113325385 B CN113325385 B CN 113325385B
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CN113325385A (en
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杨剑
胡昌华
卢建
钟都都
涂育维
姚志成
侯博
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Rocket Force University of Engineering of PLA
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/42—Diversity systems specially adapted for radar
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/36—Means for anti-jamming, e.g. ECCM, i.e. electronic counter-counter measures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/14—Fourier, Walsh or analogous domain transformations, e.g. Laplace, Hilbert, Karhunen-Loeve, transforms
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization

Abstract

The invention discloses a phased array-MIMO radar mode receiving and transmitting beam forming anti-interference method, which combines the structural characteristics of a subarray level array with the working mode of an FPMIMO radar, adopts a uniform overlapping subarray division mode for a one-dimensional array, forms signal receiving and transmitting beams in a phased array mode for each subarray in the signal receiving and transmitting process, enables the receiving signals of all subarrays to be equivalent to the receiving signals of a subarray level ULA, carries out INCM reconstruction and guide vector estimation based on the subarray level ULA, carries out virtual expansion estimation on the guide vector to form a guide vector of the receiving and transmitting beams of the FPMIMO radar, carries out virtual reconstruction by using the main characteristic vector and the characteristic value of the reconstructed INCM, obtains the virtual expansion INCM of the FPMIMO radar, and accordingly realizes the stable receiving and transmitting beam forming of the FPMIMO radar of the one-dimensional uniform overlapping subarray. The invention enhances the receiving capability of the expected signal, improves the inhibition performance of the interference signal, and has the characteristics of low side lobe, deep null, good robustness and the like.

Description

Anti-interference method for phased array-MIMO radar mode transmit-receive beam forming
Technical Field
The invention belongs to the field of array antenna beam forming, and particularly relates to an anti-interference method for receiving and transmitting a beam in a phased array-MIMO radar mode.
Background
There has been a great deal of research in the prior art in the field of transmit and receive beamforming. HPMIMO (Hybrid Phased-Multiple-Input-Multiple-Output) is a working mode of Hybrid Phased array-Multiple Input Multiple Output radar. Chinese patent CN103605122A proposes a dimension reduction self-adaptive DBF method of HPMIMO radar, which utilizes a double iteration method to calculate the optimal weight vector required by the formation of a receiving and transmitting beam, thereby reducing the calculation complexity of the weight vector obtaining process. The Twolong and other researches HPMIMO radar transmit-receive beam forming based on a full overlapping subarray division mode, and analyzes the influence of array subarray number on performance, so that an optimal subarray number determination scheme based on different criteria is obtained. Huangjunsheng et al proposed a joint transmission subarray division and beam forming design method based on two-dimensional HPMIMO radar, equally dividing the transmission array into a certain number of non-overlapping subarrays, establishing a joint optimization model about subarray structure, transmission beam weight vector and reception beam weight vector under constraint conditions with the maximum output SINR as the criterion, and solving in a loop iteration mode. However, this method requires multiple iterative optimization processes, resulting in insufficient flexibility and adaptability. In 2019, Tahcfilloh and the like divide a transmitting array and a receiving array into overlapping sub-arrays with the same array element number, adopt a Phased array mode when signals of the sub-arrays are transmitted and received, provide a working mode of a Full Phased array-Multiple Input Multiple Output (FPMIMO) radar, adopt a receiving/transmitting co-location mode, and utilize a plurality of sub-arrays to transmit various waveform combinations, thereby effectively improving coherent gain, waveform diversity gain and system flexibility. However, the FPMIMO radar is not deeply researched in the aspect of spatial filtering algorithm, and the robust design of the algorithm is lacked.
The algorithm is analyzed, and the result shows that at present, the HPMIMO radar receiving and transmitting beam forming algorithm research is mainly based on designing a subarray division method, coherent gain when signals are received is not considered by the HPMIMO radar, SINR of output signals is lower than that of the FPMIMO radar, research results on the FPMIMO radar receiving and transmitting beam forming algorithm at the present stage are extremely few, and further improvement and promotion are needed for the research on algorithm robustness and the subarray level array FPMIMO radar receiving and transmitting beam forming algorithm. Meanwhile, the generated related background requirements of engineering application provide powerful traction for developing the research of the FPMIMO radar robust transceiving beam forming algorithm.
Disclosure of Invention
The invention aims to provide an anti-interference method for receiving and transmitting beams in a phased array-MIMO radar mode, which is used for solving the problems that in the prior art, the FPMIMO radar is not deeply researched in the aspect of an airspace filtering algorithm and lacks of algorithm robustness design.
In order to realize the task, the invention adopts the following technical scheme:
an anti-interference method for forming receiving and transmitting wave beams of a phased array-MIMO radar mode is characterized in that after a receiving signal vector Z is generated through a receiving and transmitting co-located antenna, a phased array-MIMO radar receiving and transmitting wave beam y is obtained by using a formula 1MIMOSaid phased array-MIMO radar includesMThe number of the sub-arrays is equal to that of the sub-arrays,Mis a positive integer;
the formula 1 is as follows:
Figure DEST_PATH_IMAGE001
；
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE002
for the reconstructed interference-plus-noise covariance matrix,
Figure DEST_PATH_IMAGE003
，
Figure DEST_PATH_IMAGE004
a virtual extended steering vector representing the target signal,
Figure DEST_PATH_IMAGE005
to representMThe steering vectors of the individual sub-arrays,θ 0representing the target direction, i representing interference, n representing noise;
the reconstructed interference-plus-noise covariance matrix
Figure DEST_PATH_IMAGE006
Obtained by adopting a formula 2;
the formula 2 is as follows:
Figure DEST_PATH_IMAGE007
；
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE008
to represent
Figure DEST_PATH_IMAGE009
Vector of eigenvalues ofλ i To (1)qThe value of the one or more of the one,
Figure DEST_PATH_IMAGE010
representing a subarray level interference plus noise covariance matrix,
Figure DEST_PATH_IMAGE011
a steering vector representing a virtual extension of the interfering signal,
Figure DEST_PATH_IMAGE012
representing the noise power, I M Is oneM×MThe identity matrix of (1);
the receiving signal matrix Z is obtained by adopting a formula 3;
the formula 3 is as follows:
Figure DEST_PATH_IMAGE013
；
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE014
is shown asmThe channel signal processed by MF is less than or equal to 1m≤M。
Further, the said
Figure DEST_PATH_IMAGE015
Calculating by adopting a formula 4;
the formula 4 is as follows:
Figure DEST_PATH_IMAGE016
；
where FFT () represents an FFT operation, ifft () represents an inverse FFT operation,
Figure DEST_PATH_IMAGE017
representing the MF coefficients of the channel signals.
Compared with the prior art, the invention has the following technical characteristics:
(1) the invention provides a phased array-MIMO radar stable receiving and transmitting beam forming method through a one-dimensional uniform overlapping subarray division mode. In the phased array-MIMO radar, a receiving/transmitting co-located antenna mode is adopted, a sub-array mode is adopted, and the interior of each sub-array realizes the formation of transmitting and receiving beams through phase shift processing.
(2) The invention enables the sub-array level received signals to be equivalent to a uniform array received signal for guide vector estimation and utilizes Capon space spectrum estimation for interference plus noise covariance matrix (INCM) reconstruction. The received signals of all sub-arrays can be equivalent to ULA of one sub-array level. Based on the subarray-level ULA, the guide vector can be expanded into a high-dimensional virtual guide vector by estimating the guide vector, and the reconstructed INCM can be decomposed by features to reconstruct the INCM of a high-dimensional virtual array, so that the receiving and transmitting beam forming of the phased array-MIMO radar is realized.
(3) The invention effectively reduces the number of physical array elements by overlapping the array elements, simultaneously the number of sampling channels is the same as the number of sub-arrays, the hardware cost of the system is greatly reduced, the algorithm freedom degree is improved by a virtual extension mode, and the anti-interference performance is obviously enhanced.
Drawings
FIG. 1 is a schematic diagram of an array structure of a uniform overlapping subarray partition;
FIG. 2 is a graph of performance simulation under known conditions for signals DOA and INCM in an example embodiment;
FIG. 3 is a graph showing simulation of performance under conditions of known DOA and unknown INCM in the example;
FIG. 4 is a graph of performance simulation for the known conditions of INCM for signal DOA error in the example.
Detailed Description
First, technical words appearing in the present invention are explained to help better understand the technical contents of the present application:
wave beam: the electromagnetic waves emitted by a satellite antenna form a shape on the earth's surface.
Uniform Linear Array (ULA): the array antenna is formed by uniformly arranging any two adjacent antenna elements on a straight line at the same interval.
Signal plus noise covariance matrix (SNCM):
Figure DEST_PATH_IMAGE018
in the formula, X s n+(t) Representing the expected signal and noise received by the array, E { } representing the data expectation,
Figure DEST_PATH_IMAGE019
array steering vector representing a desired signal, s: (t) A vector of the desired signal is represented,
Figure DEST_PATH_IMAGE020
the sub-array level steering vectors are represented,
Figure DEST_PATH_IMAGE021
，1≤m≤M，d 0the reference array element spacing of each subarray is shown, the invention adopts a uniform overlapping subarray division mode, therefore,d 0is a half-wavelength of the signal and,cthe speed of light is indicated and is,
Figure 903530DEST_PATH_IMAGE012
representing the noise power, IMIs an M x M identity matrix,
Figure DEST_PATH_IMAGE022
indicating the angular interval in which the desired signal is located.
Interference-plus-noise covariance matrix (INCM):
Figure DEST_PATH_IMAGE023
in the formula, X i n+(t) Representing the interfering signals and noise received by the array, E { } representing the data expectation,
Figure DEST_PATH_IMAGE024
indicating correspondence by direction of interfering signalAn array flow pattern matrix formed by the guide vectors,
Figure DEST_PATH_IMAGE025
a matrix representing the incident interference signal is shown,
Figure DEST_PATH_IMAGE026
is representative of the array noise signal and is,
Figure DEST_PATH_IMAGE027
the angle interval in which the interference signal is present is the angle interval of the desired signal
Figure 335518DEST_PATH_IMAGE022
The complement of (c).
Capon spatial spectrum estimation:
Figure DEST_PATH_IMAGE028
in the formula, R represents a covariance matrix of the array reception signal.
Mf (matched filter), a matched filter, the filter with maximum output SNR when the ratio of the instantaneous power of signal to the average power of noise is maximum.
And (3) guiding vector: the array antenna has the advantages that all array elements of the array antenna form a row vector to the response of the narrow-band signal source with unit energy, and the values of the steering vector at different direction angles of the signal source are different because the array response is different at different angles.
Weight vector: in a packet communication network, when transmitting or receiving data packets, a directional antenna must obtain a weight vector corresponding to a target node for beamforming.
In this embodiment, an anti-interference method for phased array-MIMO radar mode transmit-receive beam forming is disclosed, which obtains a phased array-MIMO radar transmit-receive beam y by using equation 1 after generating a receive signal vector Z by a transmit-receive co-located antennaMIMOThe phased array-MIMO radar comprises M sub-arrays, wherein M is a positive integer;
the formula 1 is as follows:
Figure DEST_PATH_IMAGE029
；
wherein the content of the first and second substances,
Figure 505468DEST_PATH_IMAGE002
for the reconstructed interference-plus-noise covariance matrix,
Figure DEST_PATH_IMAGE030
，
Figure DEST_PATH_IMAGE031
a virtual extended steering vector representing the target signal,
Figure 290890DEST_PATH_IMAGE005
to representMThe steering vectors of the individual sub-arrays,θ 0representing the target direction, i representing interference, n representing noise;
the reconstructed interference-plus-noise covariance matrix
Figure 574104DEST_PATH_IMAGE006
Obtained by adopting a formula 2;
the formula 2 is as follows:
Figure 865408DEST_PATH_IMAGE007
；
wherein the content of the first and second substances,
Figure 601283DEST_PATH_IMAGE008
to represent
Figure 252713DEST_PATH_IMAGE009
Vector of eigenvalues ofλ i To (1)qThe value of the one or more of the one,
Figure 390433DEST_PATH_IMAGE010
representing a subarray level interference plus noise covariance matrix,
Figure 852638DEST_PATH_IMAGE011
indicating interference signalsA steering vector for a virtual extension of the number,
Figure 325077DEST_PATH_IMAGE012
representing the noise power, I M Is oneM×MThe identity matrix of (1);
the receiving signal matrix Z is obtained by adopting a formula 3;
the formula 3 is as follows:
Figure 530930DEST_PATH_IMAGE013
；
wherein the content of the first and second substances,
Figure 257578DEST_PATH_IMAGE014
is shown asmThe channel signal processed by MF is less than or equal to 1m≤M。
Specifically, the reconstructed interference plus noise covariance matrix is obtained by the following substeps:
step a: acquiring M sub-array-level ULA (ultra low power) received signals, and acquiring INCM (interferometric modulation) of the sub-array-level array according to the sub-array-level ULA received signals
Figure DEST_PATH_IMAGE032
；
Figure DEST_PATH_IMAGE033
；
Wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE034
is shown inθ l Signal power in direction;
step b: performing characteristic decomposition on the subarray level array INCM to obtain
Figure DEST_PATH_IMAGE035
；
Figure DEST_PATH_IMAGE036
；
Wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE037
representing a vector of eigenvalues
Figure DEST_PATH_IMAGE038
The diagonal matrix is formed by the two groups of the diagonal matrix,
Figure DEST_PATH_IMAGE039
representing a vector of eigenvalues, V, consisting of Q larger eigenvalues i Representative and larger eigenvalues
Figure 123640DEST_PATH_IMAGE039
A corresponding matrix of feature vectors is then generated,
Figure DEST_PATH_IMAGE040
is a feature value vector consisting of M-Q smaller feature values, V n Is related to the smaller eigenvalue
Figure 302949DEST_PATH_IMAGE040
A corresponding feature vector matrix;
Figure DEST_PATH_IMAGE041
it can also be expressed as:
Figure DEST_PATH_IMAGE042
wherein, in the step (A),
Figure DEST_PATH_IMAGE043
representing a vector of eigenvalues
Figure 437127DEST_PATH_IMAGE039
To (1)qThe value of the one or more of the one,
Figure DEST_PATH_IMAGE044
representing the second in the feature vector matrixqA column vector;
step c: will V i As a subspace of interference signals, V n Extracting noise power estimates as noise subspaces by feature decomposition
Figure 267549DEST_PATH_IMAGE012
Then, reconstructing the INCM of the virtual extended array formed by the receiving and transmitting beams of the one-dimensional uniform overlapping subarray phased array-MIMO radar to obtain
Figure DEST_PATH_IMAGE045
。
Specifically, in the phased array-MIMO radar of the present embodiment, the array thereof adopts a receiving/transmitting co-location mode, that is, the same array is used for the signal transmitting end and the signal receiving end, and the array antenna includesNAnd (3) the array element interval is half wavelength of the signal. The entire array is divided uniformly into mutually overlapping sub-arrays, each sub-array comprisingN m =N- M +1 adjacent array elements.
Specifically, the received signal matrix Z is obtained by the following substeps:
step a: the transmitting terminal forms a sub-array transmitting beam in a phase-shifting processing mode, wherein the sub-array isMA first one, whereinmAre arranged in sub-arraysθ 0The transmit waveform in the direction is:
Figure DEST_PATH_IMAGE046
in the formula (I), wherein,
Figure DEST_PATH_IMAGE047
representing the transmit power that the radar imparts to each sub-array,Prepresents the transmission power of the entire radar,s m (t) Is shown asmThe transmit waveforms of the individual sub-arrays,trepresents time, w m Is oneN m A normalized transmit weight vector of order x 1,
Figure DEST_PATH_IMAGE048
is the firstmA steering vector of each subarray;
step b: the receiving end forms a sub-array receiving beam in a phase-shifting processing mode,Mthe received signals of the sub-arrays are:
Figure DEST_PATH_IMAGE049
in the formula (I), wherein,
Figure DEST_PATH_IMAGE050
is aimed atθ 0The reflection coefficient in the direction of the light,f 0is the carrier frequency of the carrier wave,
Figure DEST_PATH_IMAGE051
is to transmit waves from the 1 st array element to the 1 st array element of the whole arraymPropagation delay of the 1 st element of a sub-array,dis the spacing between the array elements,cis the speed of light;
step c: converting the received signals of M sub-arrays into received signal vector x (x)t) Then respectively sent to MF processors for processing, and the received signals can be expandedM 2Dimension, the received signal matrix Z is obtained.
In particular, steering vector estimation at subarray level ULA
Figure DEST_PATH_IMAGE052
The method is obtained by solving an optimization model, wherein the optimization model is as follows:
Figure DEST_PATH_IMAGE053
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE054
representing a transmit signal waveform diversity vector.
Example 1
The embodiment discloses a phased array-MIMO radar mode transmit-receive beam forming anti-interference method, wherein an antenna is an ULA (ultra wideband antenna array) comprising 16 array elements, the antenna is uniformly divided into 8 mutually overlapped sub-arrays, the distance between every two adjacent array elements is half wavelength, and an expected target is positioned at an angleθ 0At 10 °, three interference targets are simultaneously present and are respectively located atθ 1=-30°，θ 2=40 ° andθ 3=60 °, and INR =40dB for all interference. In the simulation process, additive noise signals are modeled as Gaussian random with the mean value of 0 and the variance of 1The sequence and the array element noise are independently and equally distributed. The parameters of the transmitting signals are respectively set as pulse widthsT p Bandwidth of 10 μ sB=3MHZ, frequency intervalf z =3MHZ, sampling frequencyf s =20 MHZ. For the algorithm provided, the angle interval setting in which the desired signal is located during the simulation is setθ 0-5°,θ 0+5°]。
In order to fully verify the performance of the phased array-MIMO radar transmit-receive beam forming algorithm, the phased array-MIMO radar transmit-receive beam forming algorithm is matched with a traditional HPMIMO radar (HPMIMO-ES) with uniform overlapping subarray division, an HPMIMO radar (HPMIMO-US) with non-uniform division and an HPMIMO radar (HMIMOPA-CS) with a center extended subarray. For the hybrid phased array-MIMO (HPMIMO) radar participating in the test, the array elements of the receiving array and the transmitting array elements are in the similar positions, and the weight vectors are obtained according to the MVDR criterion. When input signal SNR =10dB, the comparison algorithm simulates a beam pattern; when the number of sampling continuous loops is 5, the comparison algorithm outputs a curve that SINR changes along with the signal input SNR. For each simulation scenario, the average of 200 independent Monte Carlo simulation experiments was output as the final result.
(1) Desired signal direction and virtual INCM are known
In the first simulation experiment, assuming that the INCM of the virtual extension is known or can be estimated accurately and the echo direction of the desired target is also known, the simulation experiment checks the anti-interference performance of all the participating test algorithms under preset ideal conditions.
Fig. 2(a) shows the simulation results of the transmit-receive beam patterns of all the participating test methods, and fig. 2(b) compares the variation curve of the algorithm output SINR with the signal input SNR. From the beam pattern simulation results, fig. 2(a) shows that the sidelobe level of the proposed scheme is much lower than that of other methods, the null depth in the direction of the interference signal is lower, all nulls are lower than-140 dB, but the main lobe width is slightly larger than that of other methods. For the method, the traditional beam forming algorithm is respectively applied to the transmitting and receiving processes of the subarray signals, the expected target echo signals are enhanced in the main lobe direction, the intensity of interference signals is reduced through side lobes, and the algorithm freedom degree is increased by utilizing virtual expansion. Therefore, the method can form deeper zero in the direction of the interference signal, and the anti-interference capability of the method is enhanced. Meanwhile, the simulation result of fig. 2(b) shows that the anti-interference performance of the proposed algorithm is obviously superior to that of other schemes. Therefore, the interference rejection performance of the proposed algorithm is significantly better than other schemes, with both the desired signal direction and the virtual INCM known.
(2) The desired signal direction is known but the virtual INCM is unknown
In this experiment, the interference resistance of the proposed algorithm virtual extension INCM reconstruction was examined, assuming that the direction of the expected signal is known but the virtual INCM is unknown. When the signal input SNR =0dB, fig. 3(a) gives the simulation results of the transmit-receive beam patterns of all the participating test algorithms; fig. 3(b) compares the output SINR of the algorithm with the signal input SNR when the number of sampling loops is 5. Fig. 3(a) shows that the sidelobe level of the proposed algorithm is much lower than that of other methods, and the depth of the null is deepened, which proves that the anti-interference performance of the proposed algorithm is better. Fig. 3(b) shows that SCM obtained by sampling different pulse echo signals by other methods is used to replace INCM, when the SNR of the desired signal input is increased and the interfering target is located in the same range bin as the real target, the desired signal component is inevitably mixed, which causes the self-cancellation problem, and the suppression capability of the interfering signal is obviously reduced; the proposed algorithm eliminates the influence of the expected signal under the condition of high SNR by reconstructing the virtual INCM, effectively overcomes the self-cancellation problem of the formation of the receiving and transmitting wave beams, and the output SINR of the algorithm is always kept optimal. Simulation experiments prove that the robustness of the algorithm is obviously improved by reconstructing the virtual INCM.
(3) Desired signal random direction error and virtual INCM are known
In this experiment, it is assumed that the direction of the desired signal is unknown and is inθ 0-3°,θ 0+3°]Random variation in range, while virtually extended INCM is also known, i.e. without considering the "self-cancellation" problem caused by the expected signal components, this experiment mainly examines the robustness of the algorithm in dealing with random directional errors of the signal.
In beam patternIn the simulation, it is assumed that the known target direction is
Figure DEST_PATH_IMAGE055
But the actual echo direction of the target is θ 0=10 °, under which condition all the subarray transmit beams are directed to
Figure 445458DEST_PATH_IMAGE055
And the direction of the receive beam is also θ b =13 °. When the SNR =0dB is input, as shown in fig. 4(a), the direction of the transmit-receive beam of the proposed algorithm is shifted from 13 ° to 10 °, and the specific direction is an angle therebetween, which indicates that the beam direction approaches the correct target direction through the adaptive algorithm, and the beam directions of other algorithms are all 13 ° and point to the known target direction. Experiments show that the algorithm has the capability of automatically correcting the target direction error, and the robustness of the algorithm is superior to that of other test methods. When the target direction is [7 deg. ], 13 deg. ]]When the interference direction is unknown due to random variation in the range, fig. 4(b) compares the variation curve of the algorithm output SINR with the signal SNR, and the anti-interference performance of the proposed algorithm is obviously superior to that of other methods. Therefore, when the random direction error of the signal exists, the algorithm can adaptively adjust the beam to point to the direction of the expected signal, and the robustness of the algorithm is maintained.

Claims (2)

1. An anti-interference method for forming a receiving and transmitting beam of a phased array-MIMO radar mode is characterized in that after a receiving signal matrix Z is generated through a receiving and transmitting co-located antenna, a receiving and transmitting beam y of the phased array-MIMO radar is obtained by using a formula 1MIMOSaid phased array-MIMO radar includesMThe number of the sub-arrays is equal to that of the sub-arrays,Mis a positive integer;
the formula 1 is as follows:
Figure 715291DEST_PATH_IMAGE001
；
wherein the content of the first and second substances,
Figure 641659DEST_PATH_IMAGE002
for the reconstitution of stemsThe interference-plus-noise covariance matrix is,
Figure 987190DEST_PATH_IMAGE003
，
Figure 340811DEST_PATH_IMAGE004
a virtual extended steering vector representing the target signal,
Figure 873423DEST_PATH_IMAGE005
to representMThe steering vectors of the individual sub-arrays,θ 0representing the target direction, i representing interference, n representing noise;
the reconstructed interference-plus-noise covariance matrix
Figure 104947DEST_PATH_IMAGE002
Obtained by adopting a formula 2;
the formula 2 is as follows:
Figure 39405DEST_PATH_IMAGE006
；
wherein the content of the first and second substances,
Figure 563927DEST_PATH_IMAGE007
to represent
Figure 849415DEST_PATH_IMAGE008
Vector of eigenvalues ofλ i To (1)qThe value of the one or more of the one,
Figure 852006DEST_PATH_IMAGE009
representing a subarray level interference plus noise covariance matrix,
Figure 906549DEST_PATH_IMAGE010
a steering vector representing a virtual extension of the interfering signal,
Figure 601973DEST_PATH_IMAGE011
representing work of noiseRate, I M Is oneM×MThe identity matrix of (1);
the receiving signal matrix Z is obtained by adopting a formula 3;
the formula 3 is as follows:
Figure 109178DEST_PATH_IMAGE012
；
wherein the content of the first and second substances,
Figure 915460DEST_PATH_IMAGE013
is shown asmThe channel signal processed by MF is less than or equal to 1m≤M。
2. The phased array-MIMO radar mode transmit and receive beamforming method according to claim 1 wherein said method of interference rejection is performed in accordance with a single phased array MIMO radar mode transmit and receive beamforming scheme
Figure 824510DEST_PATH_IMAGE014
Calculating by adopting a formula 4;
the formula 4 is as follows:
Figure 212807DEST_PATH_IMAGE015
；
where FFT () represents an FFT operation, ifft () represents an inverse FFT operation,
Figure 207308DEST_PATH_IMAGE016
representing the MF coefficients of the channel signals.
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